Kaohsiung Armed Forces General Hospital

Endoscopic sleeve gastroplasty (ESG) and intragastric balloon (IGB) are established endoscopic bariatric therapies (EBTs) for obesity, but their comparative efficacy and safety remain uncertain. We conducted a systematic review and meta-analysis of comparative studies evaluating ESG versus IGB. The primary outcome was percentage of total body weight loss (%TBWL), assessed at the longest available follow-up and stratified timepoints (1, 3, 6, and 12 months). To explore temporal trends, we performed a meta-regression using follow-up duration as a continuous moderator. Secondary outcomes included a meta-regression based on baseline BMI differences and a pooled analysis of adverse events. Six comparative studies (n = 5330) were included. ESG was associated with significantly greater %TBWL than IGB (mean difference: 2.541; 95% CI 0.754 to 4.327; p = 0.005), with increasing benefit over time. Meta-regression confirmed a significant positive association between follow-up duration and treatment effect (p = 0.0006). A separate meta-regression revealed greater efficacy of ESG in patients with higher baseline BMI (p = 0.0001). Overall adverse event rates were comparable between the two groups (p = 0.20) ; however, IGB showed observed trends toward higher device intolerance and early removal rates in individual cohorts. Our findings suggest that ESG may offer a therapeutic advantage over IGB regarding weight loss efficacy, a trend that appears more pronounced in cohorts with higher obesity severity and across extended follow-up periods. ESG offers a comparable safety profile to IGB and may represent a more durable endoscopic bariatric option with potential advantages in procedural tolerability. Long-term trials are needed to validate its metabolic and clinical advantages beyond 12 months.

Major depressive disorder (MDD) is a leading cause of global morbidity and mortality. Although pharmacological treatments are widely used, their effects are often limited, and nearly half of patients show resistance to current antidepressants, including those unresponsive to all available therapies. These challenges highlight the need to better understand the neurobiological mechanisms driving MDD and to develop novel therapeutic strategies, especially those involving natural compounds with multitarget actions. Baicalin, a bioactive flavonoid from Scutellaria baicalensis, exhibits antioxidant, anti-inflammatory, and neuroprotective properties and has recently gained attention for its potential to improve cognitive deficits and mood disorders. In this study, we investigated baicalin's antidepressant potential and its underlying mechanisms across multiple experimental levels. We found that oral administration of baicalin produced antidepressant-like effects in both naïve mice and those subjected to chronic restraint stress (CRS). CRS impaired hippocampal long-term potentiation (LTP), whereas baicalin restored these synaptic deficits. Importantly, intra-dorsal hippocampal microinjection of the TrkB receptor antagonist ANA-12 abolished baicalin's antidepressant effects, indicating the involvement of BDNF-TrkB signaling. Baicalin also reduced reactive oxygen species (ROS)/H2O2 production in a BDNF-associated manner, demonstrating clear antioxidant activity. Molecular docking further suggested that baicalin binds more effectively to the TrkB receptor than ANA-12, supporting its capacity to activate TrkB-mediated signaling. By integrating in vivo, ex vivo, in vitro, and in silico approaches, our study shows that baicalin exerts robust antioxidant in vitro and antidepressant effects in vivo. These benefits are primarily mediated through activation of BDNF-TrkB signaling, leading to reduced ROS/H2O2 accumulation and alleviation of CRS-induced depression-like behaviors.

Knee osteoarthritis (KOA) and sarcopenia are prevalent age-related disorders that share common pathophysiological mechanisms such as aging, chronic inflammation, and physical inactivity. Their coexistence may aggravate functional decline and disability. This cross-sectional study aimed to compare the prevalence of sarcopenia between individuals with KOA and matched controls and to explore the relationship between femoral intercondylar cartilage (FIC) thickness and muscle-related parameters. A total of 228 participants (114 KOA, 114 controls) matched by age, sex, and body mass index were enrolled. Assessments included appendicular skeletal muscle mass index (ASMMI), handgrip strength, walking speed, and physical activity. In KOA patients, ultrasound measurements of FIC and quadriceps thickness and the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) were additionally obtained. Sarcopenia prevalence was higher in the KOA group than in controls (41.2% vs. 26.3%, p = 0.017). Greater FIC thickness was associated with higher ASMMI, stronger handgrip strength, faster walking speed, and lower WOMAC pain and total scores. These findings indicate that FIC thickness may serve as a potential structural biomarker linking cartilage integrity with muscle function in KOA.

Background and Clinical Significance: We report a rare case of a 66-year-old male with malignant non-germinal center-type large B-cell lymphoma involving the thoracic epidural, cauda equina, and filum terminale simultaneously. Case Presentation: The patient complained of back pain, rapid progressive numbness, and motor palsy in both legs in one month. Neurological examination revealed grade 2 muscle power in both lower limbs, hypesthesia below the T8 dermatome, and bladder and bowel dysfunctions. Magnetic resonance imaging (MRI) with contrast showed a well-defined extradural lesion extending from the T7 to T9 level, with severe spinal cord compression. Additionally, it revealed enlargement of the cauda equina occupy-ing the extradural space from the L1‑S1 level. The lesion appeared isointense on T1, mildly hyperintense on T2-weighted images, and exhibited homogeneous enhance-ment on post-contrast images. To relieve the patient’s spinal cord compression as soon as possible and allow the patient to recover quickly after surgery, we performed uni-lateral biportal endoscopy (UBE) to completely remove the T7-9 epidural lesion. The immunohistochemical assessment confirmed a histological diagnosis of diffuse large B-cell lymphoma, a non-germinal center type. The patient received radiotherapy to the thoracic and lumbosacral areas (50 Gy) and chemotherapy with six cycles of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisolone (R-CHOP) after sur-gery. Follow-up positron emission tomography (PET) scan and MRI performed 4 months after surgery revealed complete remission of the lesion. The patient was able to walk using a walker after therapy. Conclusions: UBE is a favorable option for selected patients requiring immediate chemotherapy or radiotherapy owing to its reduced tissue trauma compared to traditional open surgery.

IntroductionEsophageal squamous cell carcinoma (ESCC) is difficult to detect early on white-light endoscopy (WLI) because lesions are subtle and artifacts (such as glare, bubbles, text, tools) mimic pathology. MethodsThis study benchmarked five object detectors including two You Only Look Once models (YOLOv5, YOLOv), Faster Region-based Convolutional Neural Networks (Faster R-CNN), Single Shot MultiBox Detector (SSD) and Real-time Detection Transformer (RT-DETR) on WLI dataset using harmonized training (from scratch, 150 epochs, identical hyperparameters) and two label configurations: a 4-label as major categories (SCC, Dysplasia, Bleeding, Inflammation) and an 11-label artifact. Evaluation used macro precision/recall/F1 at IoU 0.50 on a fixed 310-image test set. ResultsIncorporating artifact classes improved overall macro metrics, with YOLOv5/YOLOv8 providing the strongest performance in the 11-label scenarios, however, class-wise findings revealed persistent recall limitations for early disease. In the 11-label analysis, Dysplasia detection remained low (YOLOv5: 88/201, 43.8%; YOLOv8: 82/201, 40.8%), and SCC was only moderate (YOLOv5: 25/44, 56.8%; YOLOv8: 24/44, 54.5%). Confusion analyses showed that errors were dominated by non-detections (“background”) rather than misclassification with benign or artifact labels, while approximately one in five lesion predictions was a spurious unmatched false positive, implicating both sensitivity and specificity constraints. DiscussionThese results indicate that labeling artifacts reduces non-lesion confusion but does not, by itself, recover subtle early lesions. Limitations include single-center, WLI-only data and training from scratch, future work should prioritize endoscopy-specific pretraining, explicit artifact suppression or joint segmentation, and external validation.

BackgroundFerroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation, has emerged as a pivotal mechanism in cancer progression and therapeutic resistance. Concurrently, glycosylation, as a key post-translational modification, plays a critical role in regulating cell signaling, immune evasion, and metastasis. Although both processes are independently implicated in tumor biology, the intersection between ferroptosis and glycosylation remains largely unexplored.MethodsWe performed a comprehensive pan-cancer multi-omics analysis, integrating bulk transcriptomics, epigenomics, and single-cell RNA sequencing datasets. Ferroptosis and glycosylation-related genes were curated from The Molecular Signatures Database (MSigDB), leading to the identification of the metal ion transporter, SLC39A14 (solute carrier family 39 member 14), as a key intersecting gene. A ferroptosis-related gene signature was constructed using machine learning and Cox regression models, followed by survival analyses, immune microenvironment profiling, and a pathway enrichment analysis across The Cancer Genome Atlas (TCGA) cohort.ResultsSLC39A14 was found to be significantly upregulated across multiple tumor types and associated with a poor prognosis, immune-stromal infiltration, and ferroptosis resistance. Among all cancer types analyzed, glioblastoma multiforme (GBM) and kidney renal cell carcinoma (KIRC) exhibited the significantly prognostic associations and the most pronounced differential expression of SLC39A14. Single-cell analysis revealed that SLC39A14 expression was enriched between stromal and immune populations, hypoxic perivascular niches, confirming its microenvironment-specific functions. These findings were corroborated by DNA methylation data showing promoter hypomethylation of SLC39A14 in tumors compared to normal tissues. Functionally, SLC39A14 was highly enriched in pathways related to angiogenesis, the epithelial-to-mesenchymal transition, cytokine signaling, and oxidative stress adaptation including vascular endothelial growth factor (VEGF) and cell metabolism-related signaling. A nomogram integrating SLC39A14 expression with clinical parameters improved overall survival predictions.ConclusionsIn this study, we identified SLC39A14 as a dual regulator at the interface of ferroptosis and glycosylation, with significant impacts on tumor microenvironmental remodeling and therapeutic resistance. By leveraging multi-omics and single-cell transcriptomic data, we establish SLC39A14 as a promising prognostic biomarker and therapeutic target, particularly in brain and kidney cancers where ferroptosis modulation could offer novel clinical strategies.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12935-025-04003-6.

Background: Myocardial perfusion scintigraphy (MPS) is an important tool for evaluating ischemia in diabetic populations. However, applications of advanced predictive models like multivariate adaptive regression splines (MARS) to estimate summed stress scores (SSS) are lacking. Methods: In this study, 1028 diabetic women undergoing Thallium-201 MPS were analyzed. The dataset was split into training (80%) and testing (20%) subsets. MARS and multiple linear regression (MLR) models were constructed to predict SSS, and their performance was evaluated using root mean square error (RMSE), relative absolute error (RAE), root relative squared error (RRSE), Mean Absolute Percentage Error (MAPE), and Symmetric Mean Absolute Percentage Error (SMAPE). Results: On the testing dataset, the MARS model outperformed the MLR model across all metrics, with an RMSE of 3.25 compared to 3.89 for MLR, an RAE of 0.52 vs. 0.64, and an RRSE of 0.53 vs. 0.67. Similar trends were observed in MAPE (18.7% vs. 22.1%) and SMAPE (17.3% vs. 20.5%). Conclusions: The superior predictive accuracy of the MARS model suggests its potential to enhance non-invasive myocardial risk stratification in diabetic women.